CN102707619A - Fuzzy controller and method for tracking maximum solar power points - Google Patents
Fuzzy controller and method for tracking maximum solar power points Download PDFInfo
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- CN102707619A CN102707619A CN2012101669451A CN201210166945A CN102707619A CN 102707619 A CN102707619 A CN 102707619A CN 2012101669451 A CN2012101669451 A CN 2012101669451A CN 201210166945 A CN201210166945 A CN 201210166945A CN 102707619 A CN102707619 A CN 102707619A
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Abstract
The invention discloses a fuzzy controller and a method for tracking maximum solar power points. The method comprises the following steps: obtaining the sampling voltage and sampling current by sampling the output voltage and the output current of a solar cell component for every interrupt cycle; calculating the current output power of the solar cell component according to the current obtained sampling voltage and sampling current; calculating the input variable of the fuzzy controller and the variable quantity of the input variable according to the current output power, sampling voltage and the sampling current; determining turbulent step width according to the input variable and the variable quantity of the input variable; and increasing the corresponding step width based on the current reference voltage.
Description
Technical field
The present invention relates to the maximum power point tracing method of solar cell, design a kind of maximum power point tracing method (MPPT) of the solar cell based on fuzzy control especially.
Background technology
Along with the continuous acceleration of economic globalization process and the fast development of industrial economy; Worldwide energy shortage and environmental pollution have become two big key factors of restriction human social; Greatly develop the alternative energy and become the task of top priority; Solar electrical energy generation is as a kind of new electrical energy production mode, and advantages such as pollution-free, noiselessness, reusable edible are arranged, and wide development space and application prospect are arranged.
Solar electrical energy generation mainly is to utilize solar module and solar inverter to realize.Because the operating characteristic that solar module is unique, its output power is the nonlinear function of suffered intensity of sunshine, device inside junction temperature.Externally under the situation of ambient stable; There is unique maximum power point (mpp) in solar module; Therefore just need us in solar inverter, to use certain control algolithm to realize MPPT maximum power point tracking (Maximum Power Point Tracking; MPPT), no matter how external condition changes, the WV that all will adjust solar module in real time makes it to be operated near the maximum power point.
At present existing several kinds of classical maximum power point tracing methods: the one, the constant voltage tracing; This method is to set a fixing maximum power point WV in advance; When external environment changes; Still control solar module and be operated in this voltage place, this method tracking accuracy is poor, can not cause the significant amount of energy loss according to Changes in weather situation real-time follow-up.The 2nd, the disturbance observation method; This method is the output voltage with certain step-length disturbed sun ability assembly; And judge the direction of disturbance next time according to the size of output power before and after the disturbance; This method can not be taken into account quick tracking and reduce the steady state power loss, and possibly cause the DC bus-bar voltage collapse.The 3rd, the admittance method of addition; This method is to confirm through judging whether dI/dV=-I/V sets up whether solar module is operated in the maximum power point place; The precision that this method is followed the tracks of is higher; The loss of energy in the time of can effectively reducing stable state, but the hardware cost of this method is higher, and calculate comparatively complicated.
Summary of the invention
The present invention is directed to and have existing problem in the maximum power point tracing method application in the background technology now; A kind of maximum power point tracing method and used fuzzy controller of maximum power point tracking based on fuzzy control proposed; This method is a foundation with the operating characteristic of solar module; In conjunction with the advantage of fuzzy control, can reach quick tracking, reduce the stable state energy loss, prevent the effect that busbar voltage is collapsed for the good control effect that is difficult to accurate descriptive system.
Of the present inventionly be applied to that the maximum power point tracing method based on fuzzy control comprises step in the solar power system: one interrupt cycle of every interval samples to the output voltage of solar module and output current and obtains sampled voltage and sample rate current; The sampled voltage and the sample rate current that obtain according to current sampling calculate the solar module current output power; Calculate the variable quantity of input variable of fuzzy controller and input variable according to current output power, sampled voltage and sample rate current; Calculate the step-length of disturbance according to the variable quantity of input variable and input variable; Corresponding this step-length that increases on the basis of current reference voltage.
A kind of solar maximum power point of the present invention is followed the trail of used fuzzy controller; Be connected with solar power system; Be used for the maximum power point of tracking solar electricity generation system and the voltage of solar power system output is adjusted; This solar power system comprises solar module, it is characterized in that, this solar maximum power point is followed the trail of used fuzzy controller and comprised: sampling module, computing module, step-length determination module and adjusting module.Sample for the one interrupt cycle voltage and the electric current of solar module output produces a plurality of sampled voltages and a plurality of sample rate current thereby sampling module is used for every interval.Computing module is used for current sampling obtains according to sampling module sampled voltage and sample rate current calculates the solar module current output power, and the sampled voltage that obtains according to this output power, current sampling and the sample rate current variable quantity that calculates input variable of fuzzy controller and input variable.The step-length determination module is used for confirming according to the variable quantity of this input variable and input variable the step-length of disturbance.Adjusting module is used for corresponding this step-length that increases on the basis of current reference voltage.
The method of the invention biggest advantage is: on the basis that does not increase hardware cost, promptly can realize quick tracking, power loss in the time of can reducing stable state again prevents the busbar voltage collapse, increases the reliability and stability of system.This method is a foundation with the operating characteristic of solar module; According to of the influence of extraneous Changes in weather situation to the solar module output power; Calculate the direction and the step-length of disturbance in real time through FUZZY ALGORITHMS FOR CONTROL; When weather changes acutely, carry out disturbance with bigger step-length and realize following the tracks of fast; During stable state, carry out disturbance, make solar module reduce power loss near being operated in maximum power point with smaller step size.
Description of drawings
Fig. 1 is the power-voltage curve under intensity of illumination uniform temp different condition.
Fig. 2 is the power-voltage curve under the identical intensity of illumination different condition of temperature.
Fig. 3 is the module diagram that solar maximum power point is followed the trail of used fuzzy controller in the preferred embodiments of the present invention.
Fig. 4 is the obfuscation curve synoptic diagram of input, output variable.
Fig. 5 is the synoptic diagram of fuzzy reasoning table.
Fig. 6 is the process flow diagram of maximum power point tracking method during preferred embodiments of the present invention is implemented.
Embodiment
Below will combine accompanying drawing that the embodiment of the application of fuzzy control of the present invention in MPPT is described.
Fig. 1 and Fig. 2 are solar module P-V curves (working curve) under different condition.Wherein Fig. 1 is that (T1, T2, the T3) power-voltage curve under the various conditions, Fig. 2 are at temperature identical and intensity of illumination (S1, S2, S3) power-voltage curve under the various conditions in the identical and temperature of intensity of illumination.It is thus clear that along with the variation of external condition, the maximum power point of solar module can change, need follow the tracks of its maximum power point with suitable algorithm.
Fig. 3 be solar maximum power point follow the trail of used fuzzy controller 1 (below be called: module diagram fuzzy controller 1); This fuzzy controller 1 is connected with solar power system 2, is used for the maximum power point of tracking solar electricity generation system 2 and the voltage of solar power system 2 output is adjusted.Wherein, solar power system 2 comprises solar module 20 and solar inverter 21, and this solar inverter 21 is used for the dc inverter that solar module produces is become alternating current between solar module 20 and AC network.In this embodiment; This fuzzy controller 1 is digital signal processor (DSP; Digital Signal Processor), obviously, in other embodiments; This fuzzy controller 1 can be process chip such as microcontroller (Microprocessor), central processing unit (CPU, Central processing unit), single-chip microcomputer.
This fuzzy controller 1 comprises sampling module 10, computing module 11, step-length determination module 12 and adjusting module 13.Sample for the one interrupt cycle voltage and the electric current of solar module 20 outputs produces a plurality of sampled voltage V (k) and a plurality of sample rate current I (k) (wherein, k is a natural number) thereby this sampling module 10 is used for every interval.This computing module 11 is used for 10 current samplings obtain according to sampling module sampled voltage V (k) and sample rate current I (k) and calculates solar module current output power P (k)=V (k) * I (k).Sampled voltage V (k) and sample rate current I (k) that this computing module 11 also is used for obtaining according to this output power P (k), current sampling calculate input variable e (k)=(P (k)-P (k-1))/(V (k)-V (k-1)) of fuzzy controller 1 and variable quantity △ e (k)=e (k)-e (k-1) of input variable e (k).This step-length determination module 12 is used for confirming according to the variable quantity △ e (k) of this input variable e (k) and input variable the step-length △ V of disturbance.This adjusting module 13 is corresponding this step-length △ V that increases on the basis of current reference voltage, that is, and and the output voltage V ref=Vref+ △ V of adjustment solar module 20.
Concrete, as shown in Figure 4, the domain of e (k) and △ e (k) elects all that { 6 ,-4 ,-2,0,2,4,6} all adopts seven grades to cut apart, and is expressed as [NB, NM, NS, ZO, PS, PM, PB] as.The obfuscation of (whether (2) here should be removed) input and output amount: e (k), △ e (k), △ V all adopt Triangleshape grade of membership function, and its quantizing factor confirms as 9,10,30 respectively.The obfuscation curve is as shown in Figure 4.That is, as shown in Figure 4, carry out obfuscation to the variable quantity △ e (k) of input variable e (k) and input variable according to the rule of Fig. 4, to obtain the required fuzzy quantity of fuzzy controller (NB, NM; NS, ZO, PS, PM; PB representes negative big respectively, and is negative little in bearing, zero; Just little, the center, honest), obtain disturbance step-length △ V with just carrying out fuzzy reasoning after the obfuscation of these two amounts according to fuzzy reasoning table.
Please consulting Fig. 5 in the lump, is the synoptic diagram of a fuzzy reasoning table.This step-length determination module 12 also stores this fuzzy reasoning table, this fuzzy rule table definition input variable e (k), the variable quantity △ e (k) of input variable and the corresponding relation of step-length △ V.Calculate the variable quantity e (k) of input variable e (k) and input variable e (k) when this computing module 11 after, this step-length determination module 12 is confirmed this step-length △ V according to this mapping table.Thereby this adjusting module 13 is corresponding this step-length △ V that increases on the basis of reference voltage.
Wherein, the formulation of fuzzy reasoning table as shown in Figure 5, maximin (max-min) composition algorithm of employing Ma Danni (Mamdani) when carrying out the fuzzy reasoning computing, the ambiguity solution computing of output quantity is then adopted gravity model appoach commonly used and is drawn.
See also Fig. 6, be the process flow diagram of maximum power point tracking method in the preferred embodiments enforcement of the present invention.
Step S601: at first, one interrupt cycle of every interval samples to the output voltage of solar module and output current and obtains sampled voltage V (k) and sample rate current I (k);
Step S602: the sampled voltage V (k) and sample rate current I (k) voltage that obtain according to current sampling calculate solar module 20 current output power P (k)=V (k) * I (k);
Step S603: variable quantity △ e (k)=e (the k)-e (k-1) that calculates input variable e (k)=(P (k)-P (k-1))/(V (k)-V (k-1)) and e (k) according to current output power P (k), sampled voltage V (k) and sample rate current I (k);
Step S604: the variable quantity △ e (k) according to input variable e (k) and input variable e (k) passes through the step-length △ V of fuzzy controller in line computation disturbance next time;
Step S605: on the basis of current reference voltage, increase this step-length △ V accordingly, promptly adjust the reference voltage voltage Vref=Vref+ △ V of solar module.
The application of fuzzy control of the present invention in MPPT, the method online in real time adjustment disturbance step-length through fuzzy control has quick tracking concurrently and reduces the advantage that steady state power is lost, and can also increase the stability and the reliability of system simultaneously.
Above embodiment has been carried out detailed explanation to the present invention, but these are not to be construed as limiting the invention.Protection scope of the present invention is not exceeded with above-mentioned embodiment, as long as the equivalence that those of ordinary skills do according to disclosed content is modified or changed, all should include in the protection domain of putting down in writing in claims.
Claims (6)
1. a solar maximum power point is followed the trail of used fuzzy controller; Be connected with solar power system; Be used for the maximum power point of tracking solar electricity generation system and the output voltage of solar power system is adjusted; This solar power system comprises solar module, it is characterized in that, this solar maximum power point is followed the trail of used fuzzy controller and comprised:
Sampling module obtains sampled voltage and sample rate current thereby be used for sample for the one interrupt cycle voltage and the electric current of solar module output of every interval;
Computing module; Be used for current sampling obtains according to sampling module sampled voltage and sample rate current and calculate the solar module current output power, and the sampled voltage that obtains according to this output power, current sampling and the sample rate current variable quantity that calculates input variable of fuzzy controller and input variable;
The step-length determination module is used for confirming according to the variable quantity of this input variable and input variable the step-length of disturbance; Adjusting module is used for corresponding this step-length that increases on the basis of current reference voltage.
2. solar maximum power point as claimed in claim 1 is followed the trail of used fuzzy controller; It is characterized in that; This step-length determination module also stores a fuzzy reasoning table; This fuzzy rule table definition input variable, the variable quantity of input variable and the corresponding relation of step-length; Calculate the variable quantity of input variable and input variable when this computing module after, this step-length determination module obtains this fuzzy reasoning table, and confirms the corresponding step-length of variable quantity of this input variable, input variable according to this fuzzy reasoning table.
3. solar maximum power point as claimed in claim 1 is followed the trail of used fuzzy controller, it is characterized in that, it is a kind of in digital signal processor, microcontroller, central processing unit or the single-chip microcomputer that this solar maximum power point is followed the trail of used fuzzy controller.
4. solar maximum power point as claimed in claim 1 is followed the trail of used fuzzy controller; It is characterized in that; Adopt the maximin composition algorithm of Ma Danni when utilizing this fuzzy reasoning table to carry out the fuzzy reasoning computing, the ambiguity solution computing of output quantity is then adopted gravity model appoach commonly used and is drawn.
5. the method for a MPPT maximum power point tracking is used for the maximum power point of solar module is followed the tracks of and adjusted, and it is characterized in that the method comprising the steps of:
One interrupt cycle of every interval samples to the output voltage of solar module and output current and obtains sampled voltage and sample rate current;
The sampled voltage and the sample rate current that obtain according to current sampling calculate the solar module current output power;
Calculate the variable quantity of input variable of fuzzy controller and input variable according to current output power, sampled voltage and sample rate current;
Confirm the step-length of disturbance according to the variable quantity of input variable and input variable;
Corresponding this step-length that increases on the basis of current reference voltage.
6. the method for MPPT maximum power point tracking as claimed in claim 5 is characterized in that, this step " is confirmed the step-length of disturbance " and being comprised according to the variable quantity of input variable and input variable:
Obtain a fuzzy reasoning table, and confirm the corresponding step-length of variable quantity of this input variable, input variable according to this fuzzy reasoning table.
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Cited By (3)
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| TWI493317B (en) * | 2014-03-20 | 2015-07-21 | Univ Kun Shan | Solar power generation devices, solar power generation methods, maximum power tracking module and maximum power tracking control method |
| CN108803771A (en) * | 2017-05-02 | 2018-11-13 | 南京理工大学 | Maximum power point tracing method based on Adaptive Fuzzy Control |
| TWI658690B (en) * | 2017-09-15 | 2019-05-01 | 龍華科技大學 | Method for tracking maximum power of solar cell using optimized assignment function domain value |
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| EP0090212A2 (en) * | 1982-03-31 | 1983-10-05 | Siemens Aktiengesellschaft | Apparatus for automatically tracking the optimum working point of a D.C. voltage source |
| CN101572417A (en) * | 2009-06-03 | 2009-11-04 | 东南大学 | Maximum power tracking control method for monopole three-phase photovoltaic grid-connected system |
| CN101958557A (en) * | 2010-10-20 | 2011-01-26 | 深圳市科奥信电源技术有限公司 | Peak power output tracking method and system for solar battery |
| CN102136734A (en) * | 2010-09-08 | 2011-07-27 | 上海岩芯电子科技有限公司 | Method for tracing maximum power point of photovoltaic miniature grid-connected inverter |
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| EP0090212A2 (en) * | 1982-03-31 | 1983-10-05 | Siemens Aktiengesellschaft | Apparatus for automatically tracking the optimum working point of a D.C. voltage source |
| CN101572417A (en) * | 2009-06-03 | 2009-11-04 | 东南大学 | Maximum power tracking control method for monopole three-phase photovoltaic grid-connected system |
| CN102136734A (en) * | 2010-09-08 | 2011-07-27 | 上海岩芯电子科技有限公司 | Method for tracing maximum power point of photovoltaic miniature grid-connected inverter |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
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| TWI493317B (en) * | 2014-03-20 | 2015-07-21 | Univ Kun Shan | Solar power generation devices, solar power generation methods, maximum power tracking module and maximum power tracking control method |
| CN108803771A (en) * | 2017-05-02 | 2018-11-13 | 南京理工大学 | Maximum power point tracing method based on Adaptive Fuzzy Control |
| TWI658690B (en) * | 2017-09-15 | 2019-05-01 | 龍華科技大學 | Method for tracking maximum power of solar cell using optimized assignment function domain value |
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Application publication date: 20121003 |